MIT's Richard Peng, a postdoc in applied mathematics, and Michael Cohen, a graduate student in electrical engineering and computer science have developed and demonstrated an algorithm that is optimal for condensing matrices (data). Read more.

As part of the fall 2014 Assistive Technologies (6.811) class (Principles and Practices in Assistive Technologies, or PPAT), a group of EECS students teamed to develop a new way for residents of the Boston Home to communicate their needs. Since then senior Beth Hadley took on the project as her senior thesis. Read more.

EECS doctoral student Carrie Cai has devised a Google Chat extension to help users make the most of idle wait time between texts and instant-message replies. Termed WaitChatter, the app allows users to learn another language vocabulary while they wait and the app is adaptable to other IM platforms including Snapchat, Facebook, Skype and WhatsApp. Read more.

Members of the Computer Science and Artificial Intelligence Lab's (CSAIL's) Computer Graphics Group including Professors Frédo Durand and William Freeman and EECS graduate student YiChang Shih have developed an algorithm that removes reflections from photos taken through windows. Read more.

While they developed the most accurate scene recognition system, Profs. Antonio Torralba and Aude Oliva have shown how object recognition along with scene recognition could be mutually reinforcing. They will present their work at the International Conference on Learning Representations... Read more.

Is it still an either-or choice to receive (or not) all those mailing list emails? EECS graduate student Amy Zhang working with EECS Prof. David Karger in the Computer Science and Artificial Intelligence Lab's Haystack Group, has developed a new system that uses techniques from social media to give the recipient more control over his/her inbox. Read more.

Reported today by the Association for Computing Machinery (ACM), Matei Zaharia, Assistant Professor in the Department of Electrical Engineering and Computer Science and member of the Computer Science and Artificial Intelligence Lab (CSAIL) is the recipient of the 2014 ACM Doctoral Dissertation Award for his innovative solutions to tackling the surge in data processing workloads. Read more.

EECS faculty members Fredo Durand and William Freeman have teamed with Oral Buyukozturk, a professor of civil and environmental engineering at MIT, to develop an alternative technique for detecting tiny vibrations in large structures using high-speed video and computer vision techniques for magnifying motion. Read more.

Srini Devadas, the Edwin Sibley Webster Professor in MIT's Electrical Engineering and Computer Science Department and members of his group, the Computation Structures Group, have designed a process for thwarting memory-access attacks to steal data. Their scheme includes custom-built reconfigurable chips, now moving into fabrication.

Read about how Jeremy Stribling MS ’05 PhD ’09, Dan Aguayo ’01 MEng ’02 and Max Krohn PhD ’08 revealed holes in the world of scientific publications and conferences ten years ago, and how their work then still lives on.

The Society for Industrial and Applied Mathematics has named CSAIL principal investigator Charles E. Leiserson as one of its 2015 Fellows for his “enduring influence on parallel computing systems and their adoption into mainstream use through scholarly research and development.” Read more.

Students and graduates of Prof. Rob Miller's group, the User Interface Design Group have designed a system for visualizing and exploring thousands of solutions to a programming problem, ultimately enhancing online teaching and learning. Members of the group including first author and EECS graduate student Elena Glassman will present their work in April at the Association for Computing Machinery's Conference on Human Factors in Computing Systems. Read more.

Michael Stonebraker, a researcher at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) who has revolutionized the field of database management systems (DBMSs) and founded multiple successful database companies, has won the Association for Computing Machinery’s (ACM) A.M. Turing Award, often referred to as “the Nobel Prize of computing.” Read more.

Computer Science and Artificial Intelligence Laboratory (CSAIL) principal investigator and EECS Prof. Martin Rinard with members of his research group, the Center for Resilient Software, including CSAIL research scientist Stelios Sidiroglou-Douskos have developed DIODE (for Directed Integer Overflow Detection) a system to provide an effective mechanism for finding dangerous integer overflows that affect memory allocation sites in debugging code. Read more.

Former and current EECS graduate students have created new methods to automate identification of potential areas for development in rural villages in both India and sub-Saharan Africa. The group won a $10,000 prize last year from the MIT IDEAS Global Challenge. Read more.

MIT announced a major thrust toward addressing cybersecurity with the launch of three new initiatives including one focused on technology research to be based in the Computer Science and Artificial Intelligence Lab (CSAIL). Read more.

Here’s one way to get kids excited about programming: a "robot garden" with dozens of fast-changing LED lights and more than 100 origami robots that can crawl, swim, and blossom like flowers. Read more.

When MIT senior Sheldon Trotman walks into any room, he almost instinctively looks for inefficiencies. The electrical engineering and computer science major is bent on streamlining our world, and has already founded several small companies that aim to do so. Read more.

Mapping the human genome, accomplished a decade ago, was heralded for laying the foundation for understanding genetic variation and links to a wide range of diseases. But genes can be switched on and off by many chemical modifications, aka "epigenetic marks." Now Manolis Kellis, EECS professor and member of the Computer Science and Artificial Intelligence Lab and the Broad Institute has led an NIH group that has created a similar map of the human epigenome. This work will lead to a global map towards understanding fundamental developmental and disease processes in humans. Read more.

Our susceptibility to disease depends both on the genes that we inherit from our parents and on our lifetime experiences. These two components — nature and nurture — seem to affect very different processes in the context of Alzheimer's disease, according to a new study published today in the journal Nature. Read more.

In the quest for improving the speed and efficiency of multicore chips, EECS Assistant Professor Daniel Sanchez and graduate student Nathan Beckmann designed a system that moves data around multicore chips' memory banks — improving execution by 18 percent on average while increasing energy efficiency as well. They won an award for this work in 2013. Now.. Read more.

Professor Rob Miller and members of the User Interface Design Group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have devised a system that uses crowd-sourcing to annotate instructional videos for improved learning. Read more.

Five members of the Electrical Engineering and Computer Science Department of a total of eight MIT faculty have been elected to the National Academy of Engineering including Hari Balakrishnan, Sangeeta Bhatia, Anantha Chandrakasan, L. Rafael Reif and Daniela Rus. Read more.

In building multicore chips, a common inefficiency arises with the addition of more than eight cores. EECS professor Nir Shavit, principal investigator in the Computer Science and Artificial Intelligence Lab (CSAIL), a former student now at Microsoft Research and several EECS graduate students have analyzed data structures called priority codes and dodged logjams using skip code. Read more.

In a paper appearing in a forthcoming issue of the International Journal of Robotics Research, Professors and member of the Learning and Intelligent Systems Group Leslie Kaelbling and Tomas Lozano Perez and EECS graduate student Lawson Wong show that a system using an off-the-shelf algorithm to aggregate different perspectives can recognize four times as many objects as one that uses a single perspective, while reducing the number of misidentifications. Read more.